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dc.contributor.authorNeun, S
dc.contributor.authorvan Vliet, L
dc.contributor.authorHollfelder, F
dc.contributor.authorGielen, F
dc.date.accessioned2023-02-01T11:03:49Z
dc.date.issued2022-11-23
dc.date.updated2023-02-01T10:45:44Z
dc.description.abstractMicrofluidic water-in-oil emulsion droplets are becoming a mainstay of experimental biology, where they replace the classical test tube. In most applications, such as ultrahigh-throughput directed evolution, the droplet content is identical for all compartmentalized assay reactions. When emulsion droplets are used for kinetics or other functional assays, though, concentration dependencies of initial rates that define Michaelis-Menten parameters are required. Droplet-on-demand systems satisfy this need, but extracting large amounts of data is challenging. Here, we introduce a multiplexed droplet absorbance detector, which─coupled to semi-automated droplet generation─forms a tubing-based droplet-on-demand system able to generate and extract quantitative datasets from defined concentration gradients across multiple series of droplets for multiple time points. The emergence of a product is detected by reading the absorbance of the droplet sets at multiple, adjustable time points by reversing the flow direction after each detection, so that the droplets pass a line scan camera multiple times. Detection multiplexing allows absorbance values at 12 distinct positions to be measured, and enzyme kinetics are recorded for label-free concentration gradients that are composed of about 60 droplets each, covering as many concentrations. With a throughput of around 8640 data points per hour, a 10-fold improvement compared to the previously reported single point detection method is achieved. In a single experiment, 12 full datasets of high-resolution and high-accuracy Michaelis-Menten kinetics were determined to demonstrate the potential for enzyme characterization for glycosidase substrates covering a range in enzymatic hydrolysis of 7 orders of magnitude in kcat/KM. The straightforward setup, high throughput, excellent data quality, and wide dynamic range that allows coverage of diverse activities suggest that this system may serve as a miniaturized spectrophotometer for detailed analysis of clones emerging from large-scale combinatorial experiments.en_GB
dc.description.sponsorshipBiotechnology and Biological Sciences Research Council (BBSRC)en_GB
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)en_GB
dc.description.sponsorshipEuropean Union Horizon 2020en_GB
dc.description.sponsorshipEuropean Research Council (ERC)en_GB
dc.description.sponsorshipAstraZenecaen_GB
dc.format.extent16701-16710
dc.identifier.citationVol. 94, No. 48, pp. 16701-16710en_GB
dc.identifier.doihttps://doi.org/10.1021/acs.analchem.2c03164
dc.identifier.grantnumberBB/T003545/1en_GB
dc.identifier.grantnumberEP/H046593/1en_GB
dc.identifier.grantnumber685474en_GB
dc.identifier.grantnumber101000560en_GB
dc.identifier.grantnumber695669en_GB
dc.identifier.urihttp://hdl.handle.net/10871/132386
dc.identifierORCID: 0000-0003-0604-7224 (Gielen, Fabrice)
dc.language.isoenen_GB
dc.publisherAmerican Chemical Societyen_GB
dc.relation.urlhttps://www.ncbi.nlm.nih.gov/pubmed/36417687en_GB
dc.rights© 2022 The Authors. Published by American Chemical Society. Open access under a CC BY 4.0 licenceen_GB
dc.subjectEmulsionsen_GB
dc.subjectMicrofluidicsen_GB
dc.subjectKineticsen_GB
dc.subjectBiological Assayen_GB
dc.subjectHydrolysisen_GB
dc.subjectMicrofluidic Analytical Techniquesen_GB
dc.titleHigh-throughput steady-state enzyme kinetics measured in a parallel droplet generation and absorbance detection platform.en_GB
dc.typeArticleen_GB
dc.date.available2023-02-01T11:03:49Z
dc.identifier.issn0003-2700
exeter.place-of-publicationUnited States
dc.descriptionThis is the final version. Available on open access from the American Chemical Society via the DOI in this record. en_GB
dc.identifier.eissn1520-6882
dc.identifier.journalAnalytical Chemistryen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2022-10-14
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2022-11-23
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2023-02-01T10:53:56Z
refterms.versionFCDVoR
refterms.dateFOA2023-02-01T11:03:50Z
refterms.panelBen_GB
refterms.dateFirstOnline2022-11-23


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© 2022 The Authors. Published by American Chemical Society. Open access under a CC BY 4.0 licence
Except where otherwise noted, this item's licence is described as © 2022 The Authors. Published by American Chemical Society. Open access under a CC BY 4.0 licence